ArticleOsteoarthritis and cartilage open2026
Development of a population-anchored Z-score for MRI-based knee osteoarthritis disease activity: Data from the Osteoarthritis Initiative.
Article in Osteoarthritis and cartilage open, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objective: We previously developed a novel imaging biomarker, reflecting whole-knee bone marrow lesion and effusion-synovitis volumes, to measure disease activity. This study describes the process used to develop a z-score and its percentile to improve interpretability and comparability across studies. Design: We used data from several Osteoarthritis Initiative projects (n = 1084 participants with 6876 observations). For 76% of observations, participants had radiographic knee osteoarthritis (Kellgren-Lawrence grade (KL) ≥ 2). We targeted a synthetic reference population with an overall prevalence of 25% for radiographic knee osteoarthritis. A Box-Cox transformation was used to derive a standard normal distribution for a composite metric. A within-cluster resampling method was used to summarize the reference population and estimate model parameters. The new z-score was associated with categories of WOMAC knee pain to evaluate construct validity (cross-sectionally and longitudinally). Results: The probability of being a normal distribution for a Box-Cox transformed composite metric was 99.5%, and the probability that the newly developed disease activity z-score follows the standard normal distribution was 95.7%. Because increasing age was associated with an upward shift in the mean z-score distribution, we also developed an age-adjusted z-score. We found 94% consistency between the new z-score and the initial composite metric of disease activity and construct validity with WOMAC knee pain. Conclusion: The unadjusted and age-adjusted z-score for disease activity developed using a synthetic reference population improves both the statistical and clinical usefulness of the disease activity metric. This new composite metric improves comparability across studies, clinical interpretability, and statistical modeling utility.
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